Automatic Control and System Engineering, University of Sheffield
Abstract
Reproducing kernal Hilbert spaces (RKHS) provide a framework for approximation from finite data using the idea of bounded linear functionals. The approximation problem in this case can be viewed as the inverse problem of finding the optimum operator from the Euclidean space of observations to some subspace of the RKHS. In constructing the appropriate invers operator, use is made of both adjoint operators in RKHS and various norms. In this report a number of lemmas are given with respect to such adjoint operators and norms
